{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6e1ca27b-afbb-442b-8494-60bc55e7de2f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      ">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> reactants <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<\n",
      "\n",
      "    Mass Flux:         0.12 kg/m^2/s \n",
      "    Temperature:        373 K \n",
      "    Mass Fractions: \n",
      "                      H2     0.01024 \n",
      "                      O2      0.1016 \n",
      "                      AR      0.8881 \n",
      "\n",
      "\n",
      "\n",
      ">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> flame <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<\n",
      "\n",
      "    Pressure:        5066 Pa\n",
      "\n",
      "-------------------------------------------------------------------------------\n",
      "          z    velocity  spread_rate           T      lambda      eField \n",
      "-------------------------------------------------------------------------------\n",
      "          0        2.24           0         373      -50.19           0 \n",
      "       0.06     -0.1336        17.8         373      -50.19           0 \n",
      "        0.1      -1.716       29.67        1214      -50.19           0 \n",
      "       0.14      -3.298        35.6        2055      -50.19           0 \n",
      "        0.2      -5.671           0        2055      -50.19           0 \n",
      "\n",
      "-------------------------------------------------------------------------------\n",
      "          z          H2           H           O          O2          OH \n",
      "-------------------------------------------------------------------------------\n",
      "          0     0.01024           0           0      0.1016           0 \n",
      "       0.06     0.01024           0           0      0.1016           0 \n",
      "        0.1    0.005186   7.052e-06   0.0001515     0.06091    0.001018 \n",
      "       0.14   0.0001284    1.41e-05   0.0003029     0.02019    0.002035 \n",
      "        0.2   0.0001284    1.41e-05   0.0003029     0.02019    0.002035 \n",
      "\n",
      "-------------------------------------------------------------------------------\n",
      "          z         H2O         HO2        H2O2          AR          N2 \n",
      "-------------------------------------------------------------------------------\n",
      "          0           0           0           0      0.8881           0 \n",
      "       0.06           0           0           0      0.8881           0 \n",
      "        0.1     0.04459    1.92e-07   6.302e-09      0.8881           0 \n",
      "       0.14     0.08919   3.841e-07    1.26e-08      0.8881           0 \n",
      "        0.2     0.08919   3.841e-07    1.26e-08      0.8881           0 \n",
      "\n",
      "-------------------------------------------------------------------------------\n",
      "          z \n",
      "-------------------------------------------------------------------------------\n",
      "          0 \n",
      "       0.06 \n",
      "        0.1 \n",
      "       0.14 \n",
      "        0.2 \n",
      "\n",
      "\n",
      ">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> products <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<\n",
      "\n",
      "    Mass Flux:         0.06 kg/m^2/s \n",
      "    Temperature:       2055 K \n",
      "    Mass Fractions: \n",
      "                      H2   0.0001284 \n",
      "                       H    1.41e-05 \n",
      "                       O   0.0003029 \n",
      "                      O2     0.02019 \n",
      "                      OH    0.002035 \n",
      "                     H2O     0.08919 \n",
      "                     HO2   3.841e-07 \n",
      "                    H2O2    1.26e-08 \n",
      "                      AR      0.8881 \n",
      "\n",
      "\n",
      "************ Solving on 5 point grid with energy equation enabled ************\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     1.602e-05      4.599\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001825      4.948\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.004676      3.846\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.001873      3.949\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.003999      3.885\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [5] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "grid refinement disabled.\n",
      "\n",
      "******************** Solving with grid refinement enabled ********************\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [5] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 0 1 2 3 \n",
      "    to resolve AR H H2 H2O H2O2 HO2 O O2 OH T spread_rate velocity \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [9] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 0 1 2 3 4 5 6 7 \n",
      "    to resolve AR H H2 H2O H2O2 HO2 O O2 OH T spread_rate velocity \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0002563      4.894\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.004379      3.636\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.004676      3.879\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [17] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 0 1 2 3 8 9 10 11 12 13 14 15 \n",
      "    to resolve AR H H2 H2O H2O2 HO2 O O2 OH T spread_rate velocity \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0002563      4.293\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.006568       3.85\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [29] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 0 1 2 3 4 5 6 15 16 17 18 20 21 22 23 24 25 26 27 \n",
      "    to resolve AR H H2 H2O H2O2 HO2 O O2 OH T spread_rate velocity \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0003844      4.273\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.006568      4.135\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.07482      1.681\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [48] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 5 6 7 8 9 10 11 12 13 14 15 16 17 18 \n",
      "    to resolve AR H H2 H2O H2O2 HO2 O O2 OH T spread_rate velocity \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0003844      4.082\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [62] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 35 36 \n",
      "    to resolve AR H H2 H2O H2O2 HO2 O O2 OH T spread_rate velocity \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [79] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 18 19 20 21 22 23 24 25 26 27 28 29 30 31 33 34 35 36 37 38 \n",
      "    to resolve AR H H2 H2O H2O2 HO2 O O2 OH \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [99] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 25 26 27 28 35 42 43 44 45 46 50 51 52 53 54 55 \n",
      "    to resolve AR H H2O2 HO2 O \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [115] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 33 41 55 78 \n",
      "    to resolve H H2O2 HO2 \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [119] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 44 \n",
      "    to resolve H2O2 \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [120] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "no new points needed in flame\n",
      "\n",
      "Statistics:\n",
      "\n",
      " Grid   Timesteps  Functions      Time  Jacobians      Time\n",
      "    7           0       1161    0.0117         44    0.0160\n",
      "   11           0        139    0.0025          3    0.0021\n",
      "   19          30        823    0.0254         26    0.0321\n",
      "   31          20        285    0.0152         10    0.0221\n",
      "   50          30        441    0.0406         13    0.0504\n",
      "   64          10        137    0.0159          7    0.0348\n",
      "   81           0         33    0.0049          2    0.0128\n",
      "  101           0         32    0.0060          1    0.0082\n",
      "  117           0         26    0.0056          1    0.0096\n",
      "  121           0         18    0.0040          1    0.0100\n",
      "  122           0         14    0.0032          1    0.0101\n",
      "\n",
      "\n",
      ">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> reactants <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<\n",
      "\n",
      "    Mass Flux:         0.12 kg/m^2/s \n",
      "    Temperature:        373 K \n",
      "    Mass Fractions: \n",
      "                      H2     0.01024 \n",
      "                      O2      0.1016 \n",
      "                      AR      0.8881 \n",
      "\n",
      "\n",
      "\n",
      ">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> flame <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<\n",
      "\n",
      "    Pressure:        5066 Pa\n",
      "\n",
      "-------------------------------------------------------------------------------\n",
      "          z    velocity  spread_rate           T      lambda      eField \n",
      "-------------------------------------------------------------------------------\n",
      "          0        2.24  -1.674e-19         373      -44.83           0 \n",
      "    0.00375       2.234       1.401         373      -44.83           0 \n",
      "     0.0075       2.219       2.802         373      -44.83           0 \n",
      "    0.01125       2.192       4.203         373      -44.83           0 \n",
      "      0.015       2.156       5.604         373      -44.83           0 \n",
      "    0.01875       2.108       7.005         373      -44.83           0 \n",
      "    0.02062       2.081       7.705         373      -44.83           0 \n",
      "     0.0225        2.05       8.405         373      -44.83           0 \n",
      "    0.02438       2.018       9.106         373      -44.83           0 \n",
      "    0.02625       1.982       9.806         373      -44.83           0 \n",
      "    0.02812       1.944       10.51         373      -44.83           0 \n",
      "       0.03       1.903       11.21         373      -44.83           0 \n",
      "    0.03188        1.86       11.91         373      -44.83           0 \n",
      "    0.03281       1.837       12.26         373      -44.83           0 \n",
      "    0.03375       1.814       12.61         373      -44.83           0 \n",
      "    0.03469        1.79       12.96         373      -44.83           0 \n",
      "    0.03563       1.765       13.31         373      -44.83           0 \n",
      "    0.03656        1.74       13.66         373      -44.83           0 \n",
      "     0.0375       1.714       14.01         373      -44.83           0 \n",
      "    0.03797       1.701       14.18         373      -44.83           0 \n",
      "    0.03844       1.688       14.36         373      -44.83           0 \n",
      "    0.03891       1.674       14.53         373      -44.83           0 \n",
      "    0.03937       1.661       14.71       373.1      -44.83           0 \n",
      "    0.03984       1.647       14.88       373.1      -44.83           0 \n",
      "    0.04031       1.633       15.06       373.1      -44.83           0 \n",
      "    0.04078       1.619       15.24       373.2      -44.83           0 \n",
      "    0.04102       1.612       15.32       373.3      -44.83           0 \n",
      "    0.04125       1.605       15.41       373.3      -44.83           0 \n",
      "    0.04148       1.598        15.5       373.4      -44.83           0 \n",
      "    0.04172       1.591       15.59       373.5      -44.83           0 \n",
      "    0.04195       1.584       15.67       373.7      -44.83           0 \n",
      "    0.04219       1.578       15.76       373.9      -44.83           0 \n",
      "    0.04242       1.571       15.85       374.1      -44.83           0 \n",
      "    0.04266       1.565       15.94       374.4      -44.83           0 \n",
      "    0.04289       1.558       16.02       374.7      -44.83           0 \n",
      "    0.04312       1.553       16.11       375.2      -44.83           0 \n",
      "    0.04359       1.542       16.29       376.3      -44.83           0 \n",
      "    0.04406       1.533       16.47         378      -44.83           0 \n",
      "    0.04453       1.526       16.64       380.4      -44.83           0 \n",
      "      0.045       1.523       16.82       383.6      -44.83           0 \n",
      "    0.04547       1.523          17       387.8      -44.83           0 \n",
      "     0.0457       1.525        17.1       390.5      -44.83           0 \n",
      "    0.04594       1.528       17.19       393.5      -44.83           0 \n",
      "    0.04617       1.533       17.28       396.9      -44.83           0 \n",
      "    0.04641       1.539       17.37       400.9      -44.83           0 \n",
      "    0.04664       1.547       17.47       405.3      -44.83           0 \n",
      "    0.04688       1.557       17.56       410.3      -44.83           0 \n",
      "    0.04734       1.583       17.75         422      -44.83           0 \n",
      "    0.04781       1.617       17.95       435.9      -44.83           0 \n",
      "    0.04828       1.657       18.15       451.9      -44.83           0 \n",
      "    0.04875       1.703       18.35       469.8      -44.83           0 \n",
      "    0.04898       1.728       18.45       479.5      -44.83           0 \n",
      "    0.04922       1.755       18.56       489.6      -44.83           0 \n",
      "    0.04945       1.782       18.66       500.2      -44.83           0 \n",
      "    0.04969       1.811       18.77       511.2      -44.83           0 \n",
      "    0.04992       1.841       18.88       522.6      -44.83           0 \n",
      "    0.05016       1.872       18.99       534.4      -44.83           0 \n",
      "    0.05039       1.904        19.1       546.5      -44.83           0 \n",
      "    0.05063       1.937       19.21       558.9      -44.83           0 \n",
      "    0.05086        1.97       19.32       571.6      -44.83           0 \n",
      "    0.05109       2.004       19.43       584.6      -44.83           0 \n",
      "    0.05156       2.073       19.66       611.3      -44.83           0 \n",
      "    0.05203       2.143        19.9       638.8      -44.83           0 \n",
      "     0.0525       2.214       20.13         667      -44.83           0 \n",
      "    0.05344       2.359       20.62       725.1      -44.83           0 \n",
      "    0.05391       2.431       20.87       754.7      -44.83           0 \n",
      "    0.05437       2.503       21.12       784.5      -44.83           0 \n",
      "    0.05484       2.574       21.37       814.5      -44.83           0 \n",
      "    0.05531       2.644       21.62       844.4      -44.83           0 \n",
      "    0.05578       2.712       21.88         874      -44.83           0 \n",
      "    0.05625       2.779       22.14       903.1      -44.83           0 \n",
      "    0.05672       2.842        22.4       931.4      -44.83           0 \n",
      "    0.05719       2.901       22.67       958.7      -44.83           0 \n",
      "    0.05766       2.956       22.93       984.7      -44.83           0 \n",
      "    0.05812       3.006        23.2        1009      -44.83           0 \n",
      "    0.05859       3.052       23.46        1033      -44.83           0 \n",
      "    0.05906       3.092       23.73        1054      -44.83           0 \n",
      "       0.06       3.156       24.27        1093      -44.83           0 \n",
      "    0.06125       3.215       24.99        1136      -44.83           0 \n",
      "     0.0625       3.249       25.72        1172      -44.83           0 \n",
      "      0.065       3.263        27.2        1228      -44.83           0 \n",
      "     0.0675       3.235        28.7        1273      -44.83           0 \n",
      "       0.07        3.18       30.21        1312      -44.83           0 \n",
      "     0.0725       3.101       31.74        1347      -44.83           0 \n",
      "      0.075       3.004       33.29        1378      -44.83           0 \n",
      "       0.08        2.76       36.46        1433      -44.83           0 \n",
      "      0.085       2.463       39.72        1483      -44.83           0 \n",
      "       0.09       2.119       43.09        1533      -44.83           0 \n",
      "      0.095       1.733       46.62        1587      -44.83           0 \n",
      "        0.1       1.304       50.26        1650      -44.83           0 \n",
      "      0.105      0.8293       53.83        1725      -44.83           0 \n",
      "       0.11      0.3029       56.76        1811      -44.83           0 \n",
      "     0.1125     0.02056       57.64        1853      -44.83           0 \n",
      "      0.115     -0.2711       58.02        1893      -44.83           0 \n",
      "     0.1162     -0.4194       58.02        1912      -44.83           0 \n",
      "     0.1175     -0.5685        57.9        1929      -44.83           0 \n",
      "       0.12     -0.8671       57.31        1960      -44.83           0 \n",
      "     0.1225      -1.163       56.34        1985      -44.83           0 \n",
      "      0.125      -1.453       55.08        2005      -44.83           0 \n",
      "     0.1275      -1.735       53.61        2020      -44.83           0 \n",
      "       0.13      -2.007       51.98        2031      -44.83           0 \n",
      "     0.1325      -2.269       50.26        2039      -44.83           0 \n",
      "      0.135       -2.52       48.47        2044      -44.83           0 \n",
      "       0.14      -2.989        44.8        2050      -44.83           0 \n",
      "     0.1437      -3.315       42.02        2052      -44.83           0 \n",
      "     0.1475      -3.619       39.22        2053      -44.83           0 \n",
      "     0.1512      -3.901       36.42        2054      -44.83           0 \n",
      "      0.155      -4.163       33.62        2054      -44.83           0 \n",
      "     0.1587      -4.403       30.82        2054      -44.83           0 \n",
      "     0.1625      -4.623       28.02        2054      -44.83           0 \n",
      "     0.1662      -4.822       25.22        2055      -44.83           0 \n",
      "       0.17          -5       22.41        2055      -44.83           0 \n",
      "     0.1737      -5.157       19.61        2055      -44.83           0 \n",
      "     0.1775      -5.293       16.81        2055      -44.83           0 \n",
      "     0.1812      -5.409       14.01        2055      -44.83           0 \n",
      "      0.185      -5.503       11.21        2055      -44.83           0 \n",
      "     0.1888      -5.577       8.405        2055      -44.83           0 \n",
      "     0.1925      -5.629       5.604        2055      -44.83           0 \n",
      "     0.1963      -5.661       2.802        2055      -44.83           0 \n",
      "        0.2      -5.671           0        2055      -44.83           0 \n",
      "\n",
      "-------------------------------------------------------------------------------\n",
      "          z          H2           H           O          O2          OH \n",
      "-------------------------------------------------------------------------------\n",
      "          0     0.01024  -1.003e-20   8.961e-18      0.1016  -6.691e-18 \n",
      "    0.00375     0.01024  -4.453e-20   8.688e-18      0.1016  -8.379e-19 \n",
      "     0.0075     0.01024   1.934e-19   8.546e-18      0.1016  -7.304e-20 \n",
      "    0.01125     0.01024   2.576e-18   9.535e-18      0.1016   3.141e-20 \n",
      "      0.015     0.01024   3.139e-17    2.06e-17      0.1016   9.859e-20 \n",
      "    0.01875     0.01024   3.817e-16   1.205e-16      0.1016   5.941e-19 \n",
      "    0.02062     0.01024   2.017e-15   4.588e-16      0.1016   2.278e-18 \n",
      "     0.0225     0.01024   9.467e-15   2.059e-15      0.1016   1.028e-17 \n",
      "    0.02438     0.01024   4.389e-14   9.535e-15      0.1016   4.844e-17 \n",
      "    0.02625     0.01024   2.027e-13   4.403e-14      0.1016   2.374e-16 \n",
      "    0.02812     0.01024   9.335e-13   2.011e-13      0.1016   1.305e-15 \n",
      "       0.03     0.01024   4.285e-12   9.056e-13      0.1016   9.218e-15 \n",
      "    0.03188     0.01024    1.96e-11   4.015e-12      0.1016   8.642e-14 \n",
      "    0.03281     0.01024   4.764e-11   9.461e-12      0.1016   4.018e-13 \n",
      "    0.03375     0.01024   1.126e-10   2.381e-11      0.1016   1.922e-12 \n",
      "    0.03469     0.01024    2.64e-10   6.126e-11      0.1016    9.32e-12 \n",
      "    0.03563     0.01024   6.165e-10   1.581e-10      0.1016    4.46e-11 \n",
      "    0.03656     0.01024   1.435e-09   4.057e-10      0.1016   2.062e-10 \n",
      "     0.0375     0.01024   3.332e-09    1.03e-09      0.1016   9.011e-10 \n",
      "    0.03797     0.01024   5.208e-09   1.685e-09      0.1016   2.007e-09 \n",
      "    0.03844     0.01024   8.123e-09   2.815e-09      0.1016   4.466e-09 \n",
      "    0.03891     0.01024   1.264e-08   4.744e-09      0.1016   9.849e-09 \n",
      "    0.03937     0.01024   1.963e-08   8.005e-09      0.1016   2.138e-08 \n",
      "    0.03984     0.01024    3.04e-08   1.344e-08      0.1016    4.54e-08 \n",
      "    0.04031     0.01023   4.693e-08   2.237e-08      0.1016   9.381e-08 \n",
      "    0.04078     0.01023   7.223e-08   3.676e-08      0.1016   1.874e-07 \n",
      "    0.04102     0.01023   8.987e-08   4.705e-08      0.1016   2.635e-07 \n",
      "    0.04125     0.01022   1.118e-07   6.028e-08      0.1016   3.692e-07 \n",
      "    0.04148     0.01022    1.39e-07   7.719e-08      0.1016   5.142e-07 \n",
      "    0.04172     0.01022   1.728e-07   9.865e-08      0.1016   7.106e-07 \n",
      "    0.04195     0.01021   2.147e-07   1.257e-07      0.1016    9.73e-07 \n",
      "    0.04219     0.01021   2.665e-07   1.595e-07      0.1016   1.319e-06 \n",
      "    0.04242      0.0102   3.308e-07   2.016e-07      0.1016   1.771e-06 \n",
      "    0.04266      0.0102   4.103e-07   2.535e-07      0.1016   2.351e-06 \n",
      "    0.04289     0.01019   5.087e-07   3.171e-07      0.1016   3.088e-06 \n",
      "    0.04312     0.01018   6.305e-07   3.945e-07      0.1016   4.015e-06 \n",
      "    0.04359     0.01016     9.6e-07   5.975e-07      0.1016   6.541e-06 \n",
      "    0.04406     0.01014   1.455e-06   8.749e-07      0.1015   1.016e-05 \n",
      "    0.04453     0.01011   2.194e-06   1.244e-06      0.1015   1.518e-05 \n",
      "      0.045     0.01007   3.289e-06   1.725e-06      0.1014   2.194e-05 \n",
      "    0.04547     0.01003   4.897e-06   2.334e-06      0.1013   3.075e-05 \n",
      "     0.0457        0.01   5.977e-06   2.693e-06      0.1013   3.601e-05 \n",
      "    0.04594    0.009973   7.279e-06   3.095e-06      0.1012   4.189e-05 \n",
      "    0.04617     0.00994   8.844e-06    3.54e-06      0.1011   4.835e-05 \n",
      "    0.04641    0.009904   1.071e-05   4.029e-06       0.101   5.532e-05 \n",
      "    0.04664    0.009864   1.293e-05   4.561e-06      0.1009    6.27e-05 \n",
      "    0.04688    0.009821   1.556e-05   5.136e-06      0.1008   7.035e-05 \n",
      "    0.04734    0.009724   2.212e-05   6.398e-06      0.1005   8.574e-05 \n",
      "    0.04781    0.009612   3.082e-05   7.795e-06      0.1001   0.0001002 \n",
      "    0.04828    0.009483   4.209e-05   9.333e-06     0.09962   0.0001124 \n",
      "    0.04875    0.009338   5.628e-05   1.105e-05      0.0991   0.0001217 \n",
      "    0.04898    0.009258   6.471e-05   1.204e-05     0.09882   0.0001252 \n",
      "    0.04922    0.009173   7.404e-05   1.314e-05     0.09851   0.0001279 \n",
      "    0.04945    0.009084   8.431e-05    1.44e-05     0.09819   0.0001297 \n",
      "    0.04969     0.00899   9.556e-05   1.588e-05     0.09785   0.0001307 \n",
      "    0.04992     0.00889   0.0001078   1.767e-05     0.09749   0.0001309 \n",
      "    0.05016    0.008786   0.0001211   1.989e-05     0.09712   0.0001306 \n",
      "    0.05039    0.008677   0.0001355   2.269e-05     0.09672   0.0001298 \n",
      "    0.05063    0.008562   0.0001509   2.626e-05     0.09631   0.0001285 \n",
      "    0.05086    0.008443   0.0001675   3.087e-05     0.09587   0.0001271 \n",
      "    0.05109    0.008318   0.0001852   3.681e-05     0.09541   0.0001255 \n",
      "    0.05156    0.008054   0.0002237   5.363e-05     0.09441   0.0001224 \n",
      "    0.05203    0.007769   0.0002666   7.986e-05     0.09329   0.0001205 \n",
      "     0.0525    0.007462    0.000314   0.0001193       0.092   0.0001213 \n",
      "    0.05344    0.006796   0.0004199   0.0002472     0.08886   0.0001349 \n",
      "    0.05391    0.006427   0.0004795   0.0003428      0.0869   0.0001514 \n",
      "    0.05437    0.006039   0.0005425   0.0004628     0.08463   0.0001763 \n",
      "    0.05484    0.005635   0.0006081   0.0006076     0.08203   0.0002106 \n",
      "    0.05531    0.005221   0.0006752   0.0007759     0.07909   0.0002552 \n",
      "    0.05578    0.004802   0.0007425   0.0009652     0.07584   0.0003101 \n",
      "    0.05625    0.004384   0.0008086    0.001171     0.07234   0.0003747 \n",
      "    0.05672    0.003976   0.0008721    0.001389     0.06867   0.0004477 \n",
      "    0.05719    0.003584   0.0009316    0.001614     0.06492    0.000527 \n",
      "    0.05766    0.003215   0.0009858    0.001839     0.06119   0.0006102 \n",
      "    0.05812    0.002874    0.001034    0.002058     0.05758   0.0006947 \n",
      "    0.05859    0.002566    0.001075    0.002268     0.05417   0.0007784 \n",
      "    0.05906    0.002291     0.00111    0.002465     0.05102   0.0008595 \n",
      "       0.06     0.00185    0.001157    0.002807     0.04572     0.00101 \n",
      "    0.06125    0.001449    0.001185    0.003157     0.04057    0.001184 \n",
      "     0.0625    0.001205    0.001184    0.003399     0.03713    0.001337 \n",
      "      0.065    0.001017    0.001131    0.003632     0.03383    0.001589 \n",
      "     0.0675   0.0009679    0.001061    0.003707     0.03227    0.001806 \n",
      "       0.07     0.00096    0.000992     0.00371     0.03137    0.001996 \n",
      "     0.0725   0.0009604   0.0009282    0.003678     0.03072    0.002165 \n",
      "      0.075   0.0009599   0.0008696    0.003627     0.03017    0.002316 \n",
      "       0.08   0.0009506   0.0007667    0.003493     0.02925    0.002574 \n",
      "      0.085   0.0009313    0.000674    0.003328     0.02843    0.002797 \n",
      "       0.09   0.0009039   0.0005875    0.003137     0.02764    0.003001 \n",
      "      0.095   0.0008702   0.0005047    0.002923     0.02681    0.003205 \n",
      "        0.1   0.0008317   0.0004247    0.002686     0.02585    0.003429 \n",
      "      0.105   0.0007881    0.000348    0.002423     0.02467    0.003676 \n",
      "       0.11   0.0007368   0.0002768    0.002129     0.02329    0.003908 \n",
      "     0.1125   0.0007061    0.000244    0.001971     0.02258    0.003987 \n",
      "      0.115   0.0006719   0.0002135     0.00181     0.02189    0.004031 \n",
      "     0.1162   0.0006534   0.0001992     0.00173     0.02156    0.004036 \n",
      "     0.1175   0.0006342   0.0001856    0.001651     0.02125    0.004032 \n",
      "       0.12   0.0005937   0.0001605    0.001497      0.0207    0.003993 \n",
      "     0.1225   0.0005513   0.0001381    0.001352     0.02025    0.003917 \n",
      "      0.125   0.0005078   0.0001184    0.001217     0.01991     0.00381 \n",
      "     0.1275   0.0004646   0.0001011    0.001094     0.01966    0.003682 \n",
      "       0.13   0.0004227   8.619e-05   0.0009822     0.01952    0.003538 \n",
      "     0.1325    0.000383    7.34e-05   0.0008824     0.01944    0.003388 \n",
      "      0.135   0.0003462   6.255e-05   0.0007938     0.01943    0.003236 \n",
      "       0.14   0.0002826   4.574e-05   0.0006465     0.01952    0.002945 \n",
      "     0.1437   0.0002442   3.665e-05   0.0005597     0.01962     0.00275 \n",
      "     0.1475   0.0002135   2.996e-05   0.0004911     0.01974    0.002581 \n",
      "     0.1512   0.0001897   2.512e-05   0.0004382     0.01985    0.002441 \n",
      "      0.155   0.0001718   2.167e-05   0.0003985     0.01994     0.00233 \n",
      "     0.1587   0.0001587   1.926e-05   0.0003694     0.02001    0.002245 \n",
      "     0.1625   0.0001492   1.758e-05   0.0003485     0.02007    0.002181 \n",
      "     0.1662   0.0001425   1.644e-05   0.0003338     0.02011    0.002135 \n",
      "       0.17   0.0001379   1.566e-05   0.0003237     0.02013    0.002103 \n",
      "     0.1737   0.0001347   1.513e-05   0.0003167     0.02015    0.002081 \n",
      "     0.1775   0.0001326   1.478e-05   0.0003121     0.02017    0.002065 \n",
      "     0.1812   0.0001312   1.455e-05   0.0003089     0.02018    0.002055 \n",
      "      0.185   0.0001302    1.44e-05   0.0003069     0.02018    0.002048 \n",
      "     0.1888   0.0001296   1.429e-05   0.0003055     0.02019    0.002044 \n",
      "     0.1925   0.0001292   1.423e-05   0.0003046     0.02019    0.002041 \n",
      "     0.1963   0.0001289   1.418e-05    0.000304     0.02019    0.002039 \n",
      "        0.2   0.0001287   1.417e-05   0.0003034     0.02019    0.002037 \n",
      "\n",
      "-------------------------------------------------------------------------------\n",
      "          z         H2O         HO2        H2O2          AR          N2 \n",
      "-------------------------------------------------------------------------------\n",
      "          0  -5.609e-19   4.163e-19    1.95e-17      0.8881  -6.295e-71 \n",
      "    0.00375  -6.578e-18   4.113e-18    1.95e-17      0.8881  -6.295e-71 \n",
      "     0.0075  -6.917e-18   1.291e-16    1.95e-17      0.8881  -6.295e-71 \n",
      "    0.01125  -4.746e-18   1.489e-15   1.951e-17      0.8881  -6.295e-71 \n",
      "      0.015    1.76e-17    1.53e-14   1.966e-17      0.8881  -6.297e-71 \n",
      "    0.01875   2.624e-16   1.439e-13   2.162e-17      0.8881  -6.318e-71 \n",
      "    0.02062   1.293e-15   5.402e-13   3.142e-17      0.8881  -6.408e-71 \n",
      "     0.0225   7.413e-15    2.41e-12   9.919e-17      0.8881  -6.914e-71 \n",
      "    0.02438   4.337e-14   1.109e-11   5.615e-16      0.8881  -9.576e-71 \n",
      "    0.02625   2.521e-13   5.061e-11    3.67e-15      0.8881  -2.216e-70 \n",
      "    0.02812   1.446e-12   2.255e-10   2.424e-14      0.8881  -7.175e-70 \n",
      "       0.03   8.175e-12   9.648e-10   1.577e-13      0.8881  -1.939e-69 \n",
      "    0.03188   4.538e-11   3.865e-09   1.002e-12      0.8881   1.352e-69 \n",
      "    0.03281   1.254e-10   7.923e-09   3.035e-12      0.8881   3.057e-68 \n",
      "    0.03375   3.796e-10   1.747e-08    1.02e-11      0.8881   1.846e-67 \n",
      "    0.03469   1.176e-09   3.958e-08   3.501e-11      0.8881   8.565e-67 \n",
      "    0.03563   3.628e-09    8.97e-08   1.187e-10      0.8881   3.515e-66 \n",
      "    0.03656   1.103e-08   1.998e-07   3.908e-10      0.8881   1.343e-65 \n",
      "     0.0375   3.276e-08   4.301e-07    1.23e-09      0.8881   4.897e-65 \n",
      "    0.03797   5.855e-08   6.246e-07   2.234e-09      0.8881       1e-64 \n",
      "    0.03844   1.079e-07   9.184e-07   4.194e-09      0.8881    2.14e-64 \n",
      "    0.03891   2.012e-07   1.355e-06   7.948e-09      0.8881   4.675e-64 \n",
      "    0.03937   3.746e-07   1.993e-06   1.496e-08      0.8881    1.03e-63 \n",
      "    0.03984   6.914e-07   2.899e-06   2.764e-08      0.8881   2.276e-63 \n",
      "    0.04031   1.258e-06   4.146e-06   4.964e-08      0.8881   5.028e-63 \n",
      "    0.04078   2.247e-06   5.794e-06   8.592e-08      0.8881   1.108e-62 \n",
      "    0.04102   3.001e-06   6.772e-06   1.115e-07      0.8881   1.681e-62 \n",
      "    0.04125   4.025e-06   7.875e-06   1.442e-07      0.8881   2.591e-62 \n",
      "    0.04148   5.404e-06   9.096e-06   1.854e-07      0.8881   4.034e-62 \n",
      "    0.04172   7.254e-06   1.042e-05   2.365e-07      0.8882   6.315e-62 \n",
      "    0.04195   9.717e-06   1.184e-05   2.988e-07      0.8882   9.906e-62 \n",
      "    0.04219   1.298e-05   1.331e-05   3.733e-07      0.8882   1.553e-61 \n",
      "    0.04242   1.726e-05   1.479e-05   4.608e-07      0.8882   2.429e-61 \n",
      "    0.04266   2.285e-05   1.626e-05   5.616e-07      0.8882   3.785e-61 \n",
      "    0.04289   3.012e-05   1.764e-05   6.757e-07      0.8882   5.865e-61 \n",
      "    0.04312   3.949e-05   1.891e-05   8.025e-07      0.8882   9.026e-61 \n",
      "    0.04359    6.62e-05   2.092e-05   1.093e-06      0.8882   2.018e-60 \n",
      "    0.04406   0.0001061   2.223e-05   1.418e-06      0.8882   4.168e-60 \n",
      "    0.04453   0.0001641   2.287e-05   1.777e-06      0.8882   8.093e-60 \n",
      "      0.045   0.0002464   2.304e-05   2.175e-06      0.8882   1.479e-59 \n",
      "    0.04547   0.0003598   2.288e-05   2.618e-06      0.8882   2.529e-59 \n",
      "     0.0457   0.0004313   2.272e-05    2.86e-06      0.8882   3.207e-59 \n",
      "    0.04594   0.0005156    2.25e-05   3.115e-06      0.8882   4.006e-59 \n",
      "    0.04617   0.0006146   2.223e-05   3.381e-06      0.8882   4.919e-59 \n",
      "    0.04641     0.00073   2.191e-05   3.655e-06      0.8883   5.927e-59 \n",
      "    0.04664   0.0008638   2.153e-05   3.929e-06      0.8883   7.012e-59 \n",
      "    0.04688    0.001018   2.109e-05   4.191e-06      0.8883   8.124e-59 \n",
      "    0.04734     0.00139   2.005e-05   4.644e-06      0.8883    1.04e-58 \n",
      "    0.04781    0.001847   1.885e-05   4.926e-06      0.8883   1.244e-58 \n",
      "    0.04828    0.002391   1.754e-05   4.971e-06      0.8883   1.406e-58 \n",
      "    0.04875    0.003021   1.618e-05   4.753e-06      0.8883   1.524e-58 \n",
      "    0.04898    0.003371    1.55e-05   4.555e-06      0.8883   1.569e-58 \n",
      "    0.04922    0.003744   1.482e-05   4.298e-06      0.8883   1.605e-58 \n",
      "    0.04945    0.004142   1.416e-05    3.99e-06      0.8883   1.635e-58 \n",
      "    0.04969    0.004564   1.351e-05   3.645e-06      0.8883   1.659e-58 \n",
      "    0.04992    0.005011   1.288e-05   3.276e-06      0.8883   1.679e-58 \n",
      "    0.05016    0.005483   1.227e-05   2.896e-06      0.8883   1.694e-58 \n",
      "    0.05039    0.005982    1.17e-05   2.518e-06      0.8883   1.706e-58 \n",
      "    0.05063    0.006508   1.115e-05   2.153e-06      0.8883   1.715e-58 \n",
      "    0.05086    0.007065   1.062e-05   1.812e-06      0.8883   1.723e-58 \n",
      "    0.05109    0.007656   1.013e-05   1.502e-06      0.8883   1.728e-58 \n",
      "    0.05156    0.008932   9.223e-06   9.937e-07      0.8882   1.736e-58 \n",
      "    0.05203     0.01036   8.424e-06   6.235e-07      0.8881   1.738e-58 \n",
      "     0.0525     0.01199   7.723e-06   3.749e-07       0.888   1.738e-58 \n",
      "    0.05344     0.01584   6.563e-06   1.511e-07      0.8877   1.729e-58 \n",
      "    0.05391     0.01816   6.086e-06   1.002e-07      0.8875   1.723e-58 \n",
      "    0.05437     0.02079   5.662e-06   7.734e-08      0.8873   1.716e-58 \n",
      "    0.05484     0.02374    5.28e-06   6.998e-08      0.8872   1.709e-58 \n",
      "    0.05531     0.02697    4.93e-06   7.115e-08       0.887   1.702e-58 \n",
      "    0.05578     0.03045   4.605e-06   7.718e-08      0.8869   1.696e-58 \n",
      "    0.05625     0.03412   4.299e-06   8.606e-08      0.8868   1.691e-58 \n",
      "    0.05672     0.03789   4.009e-06   9.655e-08      0.8867   1.687e-58 \n",
      "    0.05719     0.04167   3.732e-06   1.077e-07      0.8867   1.684e-58 \n",
      "    0.05766     0.04537   3.471e-06   1.189e-07      0.8868   1.683e-58 \n",
      "    0.05812     0.04889   3.225e-06   1.295e-07      0.8869   1.682e-58 \n",
      "    0.05859     0.05217   2.997e-06   1.391e-07       0.887   1.682e-58 \n",
      "    0.05906     0.05516   2.788e-06   1.476e-07      0.8871   1.683e-58 \n",
      "       0.06     0.06013   2.435e-06   1.611e-07      0.8873   1.685e-58 \n",
      "    0.06125     0.06487   2.083e-06   1.736e-07      0.8876   1.688e-58 \n",
      "     0.0625     0.06796   1.835e-06   1.826e-07      0.8878   1.691e-58 \n",
      "      0.065     0.07085   1.551e-06   1.945e-07      0.8879   1.693e-58 \n",
      "     0.0675     0.07217   1.382e-06   1.991e-07       0.888   1.693e-58 \n",
      "       0.07     0.07293   1.266e-06    1.97e-07       0.888   1.692e-58 \n",
      "     0.0725      0.0735   1.176e-06   1.896e-07      0.8881   1.691e-58 \n",
      "      0.075       0.074   1.102e-06   1.789e-07      0.8881   1.687e-58 \n",
      "       0.08      0.0749   9.861e-07   1.535e-07      0.8881   1.673e-58 \n",
      "      0.085     0.07578    8.91e-07    1.27e-07      0.8881   1.638e-58 \n",
      "       0.09     0.07669   8.059e-07    1.02e-07       0.888   1.564e-58 \n",
      "      0.095     0.07767   7.222e-07    7.87e-08       0.888   1.422e-58 \n",
      "        0.1     0.07878   6.332e-07   5.753e-08       0.888    1.19e-58 \n",
      "      0.105     0.08005   5.381e-07   3.969e-08       0.888   8.778e-59 \n",
      "       0.11     0.08151   4.469e-07   2.663e-08      0.8881    5.46e-59 \n",
      "     0.1125     0.08231   4.091e-07    2.21e-08      0.8882   4.065e-59 \n",
      "      0.115     0.08313   3.791e-07   1.869e-08      0.8883   2.933e-59 \n",
      "     0.1162     0.08354   3.673e-07   1.736e-08      0.8883   2.459e-59 \n",
      "     0.1175     0.08395   3.577e-07   1.623e-08      0.8883   2.047e-59 \n",
      "       0.12     0.08474   3.442e-07    1.45e-08      0.8883   1.389e-59 \n",
      "     0.1225     0.08549   3.373e-07   1.332e-08      0.8883   9.164e-60 \n",
      "      0.125     0.08616   3.349e-07   1.254e-08      0.8883   5.895e-60 \n",
      "     0.1275     0.08675   3.354e-07   1.204e-08      0.8882    3.71e-60 \n",
      "       0.13     0.08725   3.373e-07   1.173e-08      0.8882   2.293e-60 \n",
      "     0.1325     0.08767   3.399e-07   1.154e-08      0.8882   1.401e-60 \n",
      "      0.135       0.088   3.428e-07   1.144e-08      0.8881   8.541e-61 \n",
      "       0.14     0.08848   3.488e-07   1.139e-08      0.8881   3.104e-61 \n",
      "     0.1437     0.08872   3.537e-07   1.146e-08      0.8881   1.355e-61 \n",
      "     0.1475     0.08888   3.587e-07   1.158e-08      0.8881   5.715e-62 \n",
      "     0.1512     0.08899   3.637e-07   1.174e-08      0.8881   2.334e-62 \n",
      "      0.155     0.08906   3.683e-07   1.191e-08      0.8881   9.262e-63 \n",
      "     0.1587      0.0891   3.722e-07   1.207e-08      0.8881    3.58e-63 \n",
      "     0.1625     0.08913   3.755e-07   1.221e-08      0.8881   1.352e-63 \n",
      "     0.1662     0.08915    3.78e-07   1.232e-08      0.8881       5e-64 \n",
      "       0.17     0.08917   3.799e-07   1.241e-08      0.8881   1.816e-64 \n",
      "     0.1737     0.08918   3.812e-07   1.247e-08      0.8881   6.493e-65 \n",
      "     0.1775     0.08918   3.822e-07   1.251e-08      0.8881   2.291e-65 \n",
      "     0.1812     0.08918   3.828e-07   1.254e-08      0.8881   7.993e-66 \n",
      "      0.185     0.08919   3.832e-07   1.256e-08      0.8881   2.765e-66 \n",
      "     0.1888     0.08919   3.835e-07   1.258e-08      0.8881   9.501e-67 \n",
      "     0.1925     0.08919   3.837e-07   1.259e-08      0.8881   3.251e-67 \n",
      "     0.1963     0.08919   3.838e-07   1.259e-08      0.8881   1.109e-67 \n",
      "        0.2     0.08919    3.84e-07    1.26e-08      0.8881   3.784e-68 \n",
      "\n",
      "-------------------------------------------------------------------------------\n",
      "          z \n",
      "-------------------------------------------------------------------------------\n",
      "          0 \n",
      "    0.00375 \n",
      "     0.0075 \n",
      "    0.01125 \n",
      "      0.015 \n",
      "    0.01875 \n",
      "    0.02062 \n",
      "     0.0225 \n",
      "    0.02438 \n",
      "    0.02625 \n",
      "    0.02812 \n",
      "       0.03 \n",
      "    0.03188 \n",
      "    0.03281 \n",
      "    0.03375 \n",
      "    0.03469 \n",
      "    0.03563 \n",
      "    0.03656 \n",
      "     0.0375 \n",
      "    0.03797 \n",
      "    0.03844 \n",
      "    0.03891 \n",
      "    0.03937 \n",
      "    0.03984 \n",
      "    0.04031 \n",
      "    0.04078 \n",
      "    0.04102 \n",
      "    0.04125 \n",
      "    0.04148 \n",
      "    0.04172 \n",
      "    0.04195 \n",
      "    0.04219 \n",
      "    0.04242 \n",
      "    0.04266 \n",
      "    0.04289 \n",
      "    0.04312 \n",
      "    0.04359 \n",
      "    0.04406 \n",
      "    0.04453 \n",
      "      0.045 \n",
      "    0.04547 \n",
      "     0.0457 \n",
      "    0.04594 \n",
      "    0.04617 \n",
      "    0.04641 \n",
      "    0.04664 \n",
      "    0.04688 \n",
      "    0.04734 \n",
      "    0.04781 \n",
      "    0.04828 \n",
      "    0.04875 \n",
      "    0.04898 \n",
      "    0.04922 \n",
      "    0.04945 \n",
      "    0.04969 \n",
      "    0.04992 \n",
      "    0.05016 \n",
      "    0.05039 \n",
      "    0.05063 \n",
      "    0.05086 \n",
      "    0.05109 \n",
      "    0.05156 \n",
      "    0.05203 \n",
      "     0.0525 \n",
      "    0.05344 \n",
      "    0.05391 \n",
      "    0.05437 \n",
      "    0.05484 \n",
      "    0.05531 \n",
      "    0.05578 \n",
      "    0.05625 \n",
      "    0.05672 \n",
      "    0.05719 \n",
      "    0.05766 \n",
      "    0.05812 \n",
      "    0.05859 \n",
      "    0.05906 \n",
      "       0.06 \n",
      "    0.06125 \n",
      "     0.0625 \n",
      "      0.065 \n",
      "     0.0675 \n",
      "       0.07 \n",
      "     0.0725 \n",
      "      0.075 \n",
      "       0.08 \n",
      "      0.085 \n",
      "       0.09 \n",
      "      0.095 \n",
      "        0.1 \n",
      "      0.105 \n",
      "       0.11 \n",
      "     0.1125 \n",
      "      0.115 \n",
      "     0.1162 \n",
      "     0.1175 \n",
      "       0.12 \n",
      "     0.1225 \n",
      "      0.125 \n",
      "     0.1275 \n",
      "       0.13 \n",
      "     0.1325 \n",
      "      0.135 \n",
      "       0.14 \n",
      "     0.1437 \n",
      "     0.1475 \n",
      "     0.1512 \n",
      "      0.155 \n",
      "     0.1587 \n",
      "     0.1625 \n",
      "     0.1662 \n",
      "       0.17 \n",
      "     0.1737 \n",
      "     0.1775 \n",
      "     0.1812 \n",
      "      0.185 \n",
      "     0.1888 \n",
      "     0.1925 \n",
      "     0.1963 \n",
      "        0.2 \n",
      "\n",
      "\n",
      ">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> products <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<\n",
      "\n",
      "    Mass Flux:         0.06 kg/m^2/s \n",
      "    Temperature:       2055 K \n",
      "    Mass Fractions: \n",
      "                      H2   0.0001284 \n",
      "                       H    1.41e-05 \n",
      "                       O   0.0003029 \n",
      "                      O2     0.02019 \n",
      "                      OH    0.002035 \n",
      "                     H2O     0.08919 \n",
      "                     HO2   3.841e-07 \n",
      "                    H2O2    1.26e-08 \n",
      "                      AR      0.8881 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "from pathlib import Path\n",
    "import cantera as ct\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "# parameter values\n",
    "p = 0.05 * ct.one_atm  # pressure\n",
    "T_in = 373.0  # inlet temperature\n",
    "mdot_reactants = 0.12  # kg/m^2/s\n",
    "mdot_products = 0.06  # kg/m^2/s\n",
    "rxnmech = 'h2o2.yaml'  # reaction mechanism file\n",
    "comp = 'H2:1.6, O2:1, AR:7'  # premixed gas composition\n",
    "\n",
    "width = 0.2  # m\n",
    "loglevel = 1  # amount of diagnostic output (0 to 5)\n",
    "\n",
    "# Set up the problem\n",
    "gas = ct.Solution(rxnmech)\n",
    "\n",
    "# set state to that of the unburned gas at the burner\n",
    "gas.TPX = T_in, p, comp\n",
    "\n",
    "# Create the flame simulation object\n",
    "sim = ct.CounterflowPremixedFlame(gas=gas, width=width)\n",
    "\n",
    "# Set grid refinement parameters\n",
    "sim.set_refine_criteria(ratio=3, slope=0.1, curve=0.2, prune=0.02)\n",
    "\n",
    "# set the boundary flow rates\n",
    "sim.reactants.mdot = mdot_reactants\n",
    "sim.products.mdot = mdot_products\n",
    "\n",
    "sim.set_initial_guess()  # assume adiabatic equilibrium products\n",
    "sim.show()\n",
    "\n",
    "sim.solve(loglevel, auto=True)\n",
    "\n",
    "if \"native\" in ct.hdf_support():\n",
    "    output = Path() / \"premixed_counterflow_flame.h5\"\n",
    "else:\n",
    "    output = Path() / \"premixed_counterflow_flame.yaml\"\n",
    "output.unlink(missing_ok=True)\n",
    "\n",
    "sim.save(output, name=\"mix\", description=\"solution with mixture-averaged transport\")\n",
    "\n",
    "# write the velocity, temperature, and mole fractions to a CSV file\n",
    "sim.save(\"premixed_counterflow_flame.csv\", basis=\"mole\", overwrite=True)\n",
    "sim.show_stats()\n",
    "sim.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "363fef8f-7a90-4074-964d-02b4ff5b5948",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CSV file save\n",
    "sim.save(\"premixed_counterflow_flame.csv\", basis=\"mole\", overwrite=True)\n",
    "\n",
    "# CSV file load\n",
    "data = pd.read_csv(\"premixed_counterflow_flame.csv\")\n",
    "\n",
    "# Assign variables to the corresponding columns\n",
    "distance = data[\"grid\"]       # Distance (x-axis)\n",
    "temperature = data[\"T\"]       # Temperature (K)\n",
    "h2 = data[\"X_H2\"]             # Hydrogen (H2 mole fraction)\n",
    "o2 = data[\"X_O2\"]             # Oxygen (O2 mole fraction)\n",
    "h2o = data[\"X_H2O\"]           # Water (H2O mole fraction)\n",
    "\n",
    "# Set up subplots\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 6))  # 1 row, 2 columns of subplots\n",
    "\n",
    "# Subplot 1: Temperature distribution\n",
    "axes[0].plot(distance, temperature, label=\"Temperature (K)\", color='r', linewidth=2)\n",
    "axes[0].set_xlabel(\"Distance (m)\")\n",
    "axes[0].set_ylabel(\"Temperature (K)\")\n",
    "axes[0].set_title(\"Temperature Distribution\")\n",
    "axes[0].grid()\n",
    "axes[0].legend()\n",
    "\n",
    "# Subplot 2: Species concentration profiles\n",
    "axes[1].plot(distance, h2, label=\"H2 Mole Fraction\", linewidth=2)\n",
    "axes[1].plot(distance, o2, label=\"O2 Mole Fraction\", linewidth=2)\n",
    "axes[1].plot(distance, h2o, label=\"H2O Mole Fraction\", linewidth=2)\n",
    "axes[1].set_xlabel(\"Distance (m)\")\n",
    "axes[1].set_ylabel(\"Mole Fraction\")\n",
    "axes[1].set_title(\"Species Concentration Profiles\")\n",
    "axes[1].grid()\n",
    "axes[1].legend()\n",
    "\n",
    "# Adjust layout for better spacing\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
